Improved dynamic functional connectivity estimation with an alternating hidden Markov model

Allen EA, Damaraju E, Plis SM, Erhardt EB, Eichele T, Calhoun VD (2014) Tracking whole-brain connectivity dynamics in the resting state. Cereb Cortex 24(3):663–676. https://doi.org/10.1093/cercor/bhs352

Article  PubMed  Google Scholar 

Baker AP, Brookes MJ, Rezek IA, Smith SM, Behrens T, Probert Smith PJ et al (2014) Fast transient networks in spontaneous human brain activity. Elife 3:e01867. https://doi.org/10.7554/eLife.01867

Article  PubMed  PubMed Central  Google Scholar 

Bolton TAW, Tarun A, Sterpenich V, Schwartz S, Van De Ville D (2018) Interactions between large-scale functional brain networks are captured by sparse coupled HMMs. IEEE Trans Med Imaging 37(1):230–240. https://doi.org/10.1109/TMI.2017.2755369

Article  PubMed  Google Scholar 

Bressler SL, Menon V (2010) Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn Sci 14(6):277–290. https://doi.org/10.1016/j.tics.2010.04.004

Article  PubMed  Google Scholar 

Cao B, Chen Y, Yu R, Chen L, Chen P, Weng Y et al (2019) Abnormal dynamic properties of functional connectivity in disorders of consciousness. Neuroimage Clin 24:102071. https://doi.org/10.1016/j.nicl.2019.102071

Article  PubMed  PubMed Central  Google Scholar 

Chang C, Glover GH (2010) Time-frequency dynamics of resting-state brain connectivity measured with fMRI. Neuroimage 50(1):81–98. https://doi.org/10.1016/j.neuroimage.2009.12.011

Article  PubMed  Google Scholar 

Chen B-W, Ou Y-Y, Kung C-C, Yeh D-R, Rho S, Wang J-F (2014) Multivoxel analysis for functional magnetic resonance imaging (fMRI) based on time-series and contextual information: relationship between maternal love and brain regions as a case study. Multimed Tools Appl 75(9):4851–4865. https://doi.org/10.1007/s11042-014-2020-4

Article  Google Scholar 

Dey AK, Stamenova V, Turner G, Black SE, Levine B (2016) Pathoconnectomics of cognitive impairment in small vessel disease: A systematic review. Alzheimers Dement 12(7):831–845. https://doi.org/10.1016/j.jalz.2016.01.007

Article  PubMed  Google Scholar 

Erhardt EB, Allen EA, Wei Y, Eichele T, Calhoun VD (2012) SimTB, a simulation toolbox for fMRI data under a model of spatiotemporal separability. Neuroimage 59(4):4160–4167. https://doi.org/10.1016/j.neuroimage.2011.11.088

Article  PubMed  Google Scholar 

Fortunato S (2010) Community detection in graphs. Phys Rep 486(3–5):75–174. https://doi.org/10.1016/j.physrep.2009.11.002

Article  Google Scholar 

Friston KJ (2011) Functional and effective connectivity: a review. Brain Connect 1(1):13–36. https://doi.org/10.1089/brain.2011.0008

Article  PubMed  Google Scholar 

Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL et al (2013) The minimal preprocessing pipelines for the human connectome project. Neuroimage 80:105–124. https://doi.org/10.1016/j.neuroimage.2013.04.127

Article  PubMed  Google Scholar 

Handwerker DA, Roopchansingh V, Gonzalez-Castillo J, Bandettini PA (2012) Periodic changes in fMRI connectivity. Neuroimage 63(3):1712–1719. https://doi.org/10.1016/j.neuroimage.2012.06.078

Article  PubMed  Google Scholar 

Hawkins DM (2004) The problem of overfitting. J Chem Inf Comput Sci 44(1):1–12

Article  CAS  PubMed  Google Scholar 

Papma JM, den Heijer T, de Koning I, Mattace-Raso FU, van der Lugt A, van der Lijn F et al (2012) The influence of cerebral small vessel disease on default mode network deactivation in mild cognitive impairment. Neuroimage Clin 2:33–42. https://doi.org/10.1016/j.nicl.2012.11.005

Article  PubMed  PubMed Central  Google Scholar 

Preti MG, Bolton TA, Van De Ville D (2017) The dynamic functional connectome: state-of-the-art and perspectives. Neuroimage 160:41–54. https://doi.org/10.1016/j.neuroimage.2016.12.061

Article  PubMed  Google Scholar 

Rabiner LR (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proc IEEE 77(2):257–286

Article  Google Scholar 

Rezek I, Roberts S (2005) Ensemble hidden markov models with extended observation densities for Biosignal Analysis. In: Husmeier D, Dybowski R, Roberts S (eds) Probabilistic modeling in bioinformatics and Medical Informatics. Adv Inf Knowl Process. Springer, London. https://doi.org/10.1007/1-84628-119-9_14

Chapter  Google Scholar 

Sendi MSE, Zendehrouh E, Miller RL, Fu Z, Du Y, Liu J et al (2020) Alzheimer’s disease projection from normal to mild dementia reflected in functional network connectivity: a longitudinal study. Front Neural Circuits 14:593263. https://doi.org/10.3389/fncir.2020.593263

Article  PubMed  Google Scholar 

Shirer WR, Ryali S, Rykhlevskaia E, Menon V, Greicius MD (2012) Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cereb Cortex 22(1):158–165. https://doi.org/10.1093/cercor/bhr099

Article  CAS  PubMed  Google Scholar 

Smith RX, Jann K, Ances B, Wang DJ (2015) Wavelet-based regularity analysis reveals recurrent spatiotemporal behavior in resting-state fMRI. Hum Brain Mapp 36(9):3603–3620. https://doi.org/10.1002/hbm.22865

Article  PubMed  PubMed Central  Google Scholar 

Taghia J, Ryali S, Chen T, Supekar K, Cai W, Menon V (2017) Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI. Neuroimage 155:271–290. https://doi.org/10.1016/j.neuroimage.2017.02.083

Article  PubMed  Google Scholar 

Tagliazucchi E, Balenzuela P, Fraiman D, Chialvo DR (2012) Criticality in large-scale brain FMRI dynamics unveiled by a novel point process analysis. Front Physiol 3:15. https://doi.org/10.3389/fphys.2012.00015

Article  PubMed  PubMed Central  Google Scholar 

Tian L, Li Q, Wang C, Yu J (2018) Changes in dynamic functional connections with aging. Neuroimage 172:31–39. https://doi.org/10.1016/j.neuroimage.2018.01.040

Article  PubMed  Google Scholar 

Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N et al (2002) Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 15(1):273–289. https://doi.org/10.1006/nimg.2001.0978

Article  CAS  PubMed  Google Scholar 

Vidaurre D (2021) A new model for simultaneous dimensionality reduction and time-varying functional connectivity estimation. PLoS Comput Biol 17(4):e1008580. https://doi.org/10.1371/journal.pcbi.1008580

Article  CAS  PubMed  PubMed Central  Google Scholar 

Vidaurre D, Quinn AJ, Baker AP, Dupret D, Tejero-Cantero A, Woolrich MW (2016) Spectrally resolved fast transient brain states in electrophysiological data. Neuroimage 126:81–95. https://doi.org/10.1016/j.neuroimage.2015.11.047

Article  PubMed  Google Scholar 

Vidaurre D, Smith SM, Woolrich MW (2017) Brain network dynamics are hierarchically organized in time. Proc Natl Acad Sci U S A 114(48):12827–12832. https://doi.org/10.1073/pnas.1705120114

Article  CAS  PubMed  PubMed Central  Google Scholar 

Vidaurre D, Abeysuriya R, Becker R, Quinn AJ, Alfaro-Almagro F, Smith SM et al (2018) Discovering dynamic brain networks from big data in rest and task. Neuroimage 180(Pt B):646–656. https://doi.org/10.1016/j.neuroimage.2017.06.077

Article  PubMed  Google Scholar 

Wang S, Wen H, Hu X, Xie P, Qiu S, Qian Y et al (2020) Transition and dynamic reconfiguration of whole-brain network in major depressive disorder. Mol Neurobiol 57(10):4031–4044. https://doi.org/10.1007/s12035-020-01995-2

Article  CAS  PubMed  Google Scholar 

Xu Y, Lindquist MA (2015) Dynamic connectivity detection: an algorithm for determining functional connectivity change points in fMRI data. Front Neurosci 9:285. https://doi.org/10.3389/fnins.2015.00285

Article  PubMed  PubMed Central  Google Scholar 

Zhang G, Cai B, Zhang A, Stephen JM, Wilson TW, Calhoun VD et al (2020) Estimating dynamic functional brain connectivity with a sparse hidden markov model. IEEE Trans Med Imaging 39(2):488–498. https://doi.org/10.1109/TMI.2019.2929959

Article  PubMed  Google Scholar 

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